Spatial distribution of clusters of HFRS with significant higher incidence using the maximum cluster size 30% of the total population in Liaoning Province, China, 2000–2005

<p><b>Copyright information:</b></p><p>Taken from "Analysis of the geographic distribution of HFRS in Liaoning Province between 2000 and 2005"</p><p>http://www.biomedcentral.com/1471-2458/7/207</p><p>BMC Public Health 2007;7():207-207.</p><p>Published online 15 Aug 2007</p><p>PMCID:PMC2194774.</p><p></p

Spatial smoothed percentile map of HFRS in Liaoning Province, China, 2000–2005

<p><b>Copyright information:</b></p><p>Taken from "Analysis of the geographic distribution of HFRS in Liaoning Province between 2000 and 2005"</p><p>http://www.biomedcentral.com/1471-2458/7/207</p><p>BMC Public Health 2007;7():207-207.</p><p>Published online 15 Aug 2007</p><p>PMCID:PMC2194774.</p><p></p

Spatial distribution of clusters of HFRS with significant higher incidence using the maximum cluster size 50% of the total population in Liaoning Province, China, 2000–2005

<p><b>Copyright information:</b></p><p>Taken from "Analysis of the geographic distribution of HFRS in Liaoning Province between 2000 and 2005"</p><p>http://www.biomedcentral.com/1471-2458/7/207</p><p>BMC Public Health 2007;7():207-207.</p><p>Published online 15 Aug 2007</p><p>PMCID:PMC2194774.</p><p></p

Comparison of Two Hybrid Models for Forecasting the Incidence of Hemorrhagic Fever with Renal Syndrome in Jiangsu Province, China

<div><p>Background</p><p>Cases of hemorrhagic fever with renal syndrome (HFRS) are widely distributed in eastern Asia, especially in China, Russia, and Korea. It is proved to be a difficult task to eliminate HFRS completely because of the diverse animal reservoirs and effects of global warming. Reliable forecasting is useful for the prevention and control of HFRS.</p><p>Methods</p><p>Two hybrid models, one composed of nonlinear autoregressive neural network (NARNN) and autoregressive integrated moving average (ARIMA) the other composed of generalized regression neural network (GRNN) and ARIMA were constructed to predict the incidence of HFRS in the future one year. Performances of the two hybrid models were compared with ARIMA model.</p><p>Results</p><p>The ARIMA, ARIMA-NARNN ARIMA-GRNN model fitted and predicted the seasonal fluctuation well. Among the three models, the mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of ARIMA-NARNN hybrid model was the lowest both in modeling stage and forecasting stage. As for the ARIMA-GRNN hybrid model, the MSE, MAE and MAPE of modeling performance and the MSE and MAE of forecasting performance were less than the ARIMA model, but the MAPE of forecasting performance did not improve.</p><p>Conclusion</p><p>Developing and applying the ARIMA-NARNN hybrid model is an effective method to make us better understand the epidemic characteristics of HFRS and could be helpful to the prevention and control of HFRS.</p></div

Monthly HFRS incidence series of Jiangsu province in China from January 2004 to December 2012.

<p>Monthly HFRS incidence series of Jiangsu province in China from January 2004 to December 2012.</p

The selection of the optimal spread of the ARIMA-GRNN hybrid model.

<p>When the spread was 0.006, the RMSE for the testing samples is the least.</p

The time series response plot of target series.

<p>This plot displays the inputs, targets and errors versus time. In the training, validation and testing samples the errors were small. We assured that the model was suitable.</p

Parameter estimates and their testing resulting of the final seasonal ARIMA (0,1,1)×(0,1,1)₁₂ model.

<p>Parameter estimates and their testing resulting of the final seasonal ARIMA (0,1,1)×(0,1,1)₁₂ model.</p

The observed HFRS incidence and modeling and forecasting values simulated by ARIMA, ARIMA-NARNN and ARIMA-GRNN model.

<p>The data set was divided into modeling and forecasting data set with a vertical line; the left is the modeling stage, and the right is the forecasting stage.</p

Seroprevalence of Antibodies to Highly Pathogenic Avian Influenza A (H5N1) Virus among Close Contacts Exposed to H5N1 Cases, China, 2005–2008

<div><p>To assess the extent of highly pathogenic avian influenza (HPAI) A (H5N1) virus transmission, we conducted sero-epidemiologic studies among close contacts exposed to H5N1 cases in mainland China during 2005–2008. Blood specimens were collected from 87 household members and 332 social contacts of 23 H5N1 index cases for HPAI H5N1 serological testing by modified horse red-blood-cell hemagglutinin inhibition and microneutralization assays. All participants were interviewed with a standardized questionnaire to collect information about the use of personal protective equipment, illness symptoms, exposure to an H5N1 case during the infectious period, and poultry exposures. Two (2.3%) household contacts tested positive for HPAI H5N1 virus antibody, and all social contacts tested negative. Both seropositive cases had prolonged, unprotected, close contact with a different H5N1 index case, including days of bed-care or sleeping together during the index case’s infectious period, and did not develop any illness. None of the 419 close contacts used appropriate personal protective equipment including 17% who reported providing bedside care or having physical contact with an H5N1 case for at least 12 hours. Our findings suggest that HPAI H5N1 viruses that circulated among poultry in mainland China from 2005–2008 were not easily transmitted to close contacts of H5N1 cases.</p></div